Method for inverting aerosol components using lidar ratio and depolarization ratio

ABSTRACT

The present disclosure discloses a method for inverting aerosol components using a LiDAR ratio and a depolarization ratio, including: S1. identifying sand dust, a spherical aerosol and a mixture of the sand dust and the spherical aerosol based on a depolarization ratio; S2. calculating a proportion of the sand dust in the mixture of the sand dust and the spherical aerosol; and S3. identifying soot and a water-soluble aerosol in the spherical aerosol based on a LiDAR ratio. In the present disclosure, only a wavelength with a polarization channel is needed, to identify the aerosol components, achieving high accuracy with low detection costs.

TECHNICAL FIELD

The present disclosure relates to the technical field of atmosphericenvironment monitoring, and in particular, to a method for invertingaerosol components using a LiDAR ratio and a depolarization ratio.

BACKGROUND ART

A LiDAR ratio (S) is a ratio of an extinction coefficient to abackscattering coefficient, and is calculated using an equation:

S _(i)=σ_(i)/β_(i)   (1),

where i represents different aerosol components; σ_(i) representsextinction coefficients of the different components; β_(i) representsbackscattering coefficients of the different components. The LiDAR ratiois an important parameter for identifying aerosol components. Differenttypes of aerosols have significantly different LiDAR ratios. Asdisclosed in previous study, sand-dust particles from Asia or the Saharahave a LiDAR ratio of approximately 50 sr (Burton et al., 2012; Murayamaet al., 2004). LiDAR ratios of pure sand-dust particles are differentmainly due to their different source regions. Based on observed results,usually, aerosol particles with stronger absorbency, such as blackcarbon (BC), have larger LiDAR ratios that mainly range from 70 sr to 80sr (Burton et al., 2012; Mueller et al., 2007). In the case thatdischarge of waste causes pollution in the region, haze particlesusually have LiDAR ratios that mainly ranges from 45 sr to 60 sr(Mueller et al., 2007; Tesche et al., 2007; Xie et al., 2008). The valueis close to the LiDAR ratio of the sand-dust particles, and therefore,to accurately separate the sand dust from water-soluble aerosolparticles, other LiDAR parameters are still needed.

The depolarization ratio (δ) is a ratio of a vertical polarizationcomponent to a horizontal polarization component of a LiDAR signal, andis calculated using an equation:

δ=P _(r) /P _(l)   (2),

where P_(r) and P_(l) are separately the vertical polarization componentand the horizontal polarization component of the signal. A NIESMiescattering LiDAR system has a polarizer with a 45° polarizationdirection for a 532 nm signal, which can separate a horizontal signalfrom a vertical signal. The depolarization ratio is a parameter that candirectly reflect a shape of the aerosol particles. The greater thedepolarization ratio, the more irregular the particle shape. Accordingto laboratory results by Sakai et al. (2010), sand-dust particles mainlyin a coarse mode have a depolarization ratio of 0.39±0.04 for the 532 nmsignal. This is consistent with a characteristic of sand-dust particlesdetected outside the laboratory, and the sand-dust particles from Asiaor the Sahara has a depolarization ratio of approximately 0.3 to 0.35(Burton et al., 2012; Groß et al., 2011; Xie et al., 2008). However,aerosols in urban regions and absorptive aerosols produced aftercombustion of biological substances have a smaller size and a smallerdepolarization ratio, which is usually less than 0.1 to 0.2 (Burton etal., 2012; Mamouri and Ansmann, 2014; Sakai et al., 2010; Xie et al.,2008). Therefore, it is believed that a material having a depolarizationratio of 0.2 to 0.35 is a mixture of the sand dust and other substances.

The Miescattering theory is proposed with respect to scattering ofhomogeneous spherical particles, and is derived from Maxwell's equationsas an exact solution to scattering of plane waves by the homogeneousspherical particles in an electromagnetic field. Usually, scatteringcaused by microparticles whose particle diameter is equivalent to awavelength of incident light is referred to as Miescattering. Whenparticle diameter distribution and complex refractive indexes ofdifferent types of aerosols are provided, an extinction coefficient anda backscattering coefficient of different aerosol components can becalculated according to the Miescattering theory, so as to obtain aLiDAR ratio of different types of aerosols.

Derived from the Miescattering theory, both expressions of abackscattering efficiency factor Q_(b) and an extinction efficiencyfactor Q_(e) of a single spherical particle are as follows:

$\begin{matrix}{Q_{e} = {\frac{2}{x^{2}}{\sum_{n = 1}^{\infty}{\left( {{2n} + 1} \right){{Re}\left( {a_{n} + b_{n}} \right)}}}}} & (3)\end{matrix}$ $\begin{matrix}{Q_{b} = {\frac{1}{x^{2}}{❘{\sum_{n = 1}^{\infty}{\left( {{2n} + 1} \right)\left( {- 1} \right)^{n}\left( {a_{n} - b_{n}} \right)^{2}}}❘}}} & (4)\end{matrix}$

where

${x = \frac{2\pi r}{\lambda}},$

r represents a particle radius, λ represents a laser wavelength; anda_(n) and b_(n) represent complex coefficients and are related to theparticle radius and a negative refractive index. Therefore, to calculatethe extinction efficiency factor and the backscattering efficiencyfactor of the single particle, only the particle radius and the complexrefractive index are required.

The extinction coefficient and the backscattering coefficient ofaerosols of a specific mass concentration can be further calculatedbased on calculated values of Q_(e) and Q_(b). In this way, when theparticle size distribution remains unchanged, the extinction coefficientand the backscattering coefficient (measured in m⁻¹) of atmosphericaerosols can be determined. Expressions of the extinction coefficientβ_(e) and the backscattering coefficient β_(b) are as follows:

$\begin{matrix}{\beta_{e} = {\int_{+ \infty}^{- \infty}{\frac{3}{4r}\frac{{dV}(r)}{d\ln r}{Q_{e}\left( {\frac{2\pi r}{\lambda},m} \right)}d\ln{r.}}}} & (5)\end{matrix}$ $\begin{matrix}{\beta_{b} = {\int_{+ \infty}^{- \infty}{\frac{3}{4r}\frac{{dV}(r)}{d\ln r}{Q_{b}\left( {\frac{2\pi r}{\lambda},m} \right)}d\ln r}}} & (6)\end{matrix}$

where

$\frac{{dV}(r)}{dlnr}$

represents aerosol volume distribution:

$\begin{matrix}{{\frac{{dV}(r)}{dlnr} = {\frac{V_{0}}{\sqrt{2\pi}\ln\sigma}{\exp\left( {{- \frac{1}{2}}\left( \frac{{\ln r} - {\ln r_{v}}}{\ln\sigma} \right)^{2}} \right)}}},} & (7)\end{matrix}$

V₀ represents a total volume concentration of aerosol particles; r_(v)represents a volume geometric mean radius; and σ represents a volumestandard deviation.

Table 1 shows a LiDAR ratio obtained based on particle size distributionand complex refractive indexes of three aerosols of soot (mainlyabsorbing aerosol BC), the water-soluble aerosol (mainly sulfate andnitrate), and the sand dust provided in a previous study (Dey et al.,2006; Ganguly et al., 2009; Hess et al., 1998; van Beelen et al., 2014)with reference to the Miescattering theory. It can be found that theLiDAR ratio of the soot is approximately twice that of the water-solubleaerosol, and therefore, the soot and the water-soluble aerosol can beidentified using the LiDAR ratios. However, due to sphere assumption inthe Miescattering theory, the calculated LiDAR ratio of the sand dust isnot consistent with an actual result in field observation. During actualobservation, the sand dust is usually an irregular non-sphericalparticle. It should be noted that the actually observed LiDAR ratio(Burton et al., 2012; Murayama et al., 2004) is close to that of thewater-soluble aerosol, but the sand dust and the water-soluble aerosolhave significantly different depolarization ratios. Therefore, in aninversion algorithm, the sand dust can be first separated from thespherical aerosol using a non-spherical characteristic of the sand dust,and then the soot can be distinguished from the water-soluble aerosolusing significantly different LiDAR ratios.

TABLE 1 Microphysical paramaeters used in an inversion algorithm typer_(m) s_(d) m_(r) m_(i) S δ reference Soot 0.095 1.8 1.85 0.71 85 0.05Ganguly et al. (2009) van Beelen et al. (2014) Burton et al. (2012)Water- 0.17 2 1.53   1 × 10⁻⁷ 47 0.05 Ganguly et al. (2209) soluble vanBeelen et al. (2014) and Dey et al. (2006) and Sugimoto et al. (2003)Dust 3 2.2 1.53 6.3 × 10⁻³ 21 0.31 van Beelen et al. (2014) and Hess etal. (1998) and Mamouri et. al. (2014)

Herein, r_(m) represents a volume average radius (measured in um); s_(d)represents the volume standard deviation (measured in um); m_(r)represents a real part of the complex refractive index; m_(i) representsan imaginary part of the complex refractive index; S represents theLiDAR ratio; and δ represents the depolarization ratio.

SUMMARY

To solve the technical problems, the present disclosure provides amethod for inverting aerosol components using a LiDAR ratio and adepolarization ratio, providing a feasible technical solution for avertical study on aerosol components during atmospheric environmentmonitoring.

To solve the above technical problems, the present disclosure providesthe following technical solutions:

A method for inverting aerosol components using a LiDAR ratio and adepolarization ratio is provided, including:

S1. identifying sand dust, a spherical aerosol and a mixture of the sanddust and the spherical aerosol based on a depolarization ratio;

S2. calculating a proportion of the sand dust in the mixture of the sanddust and the spherical aerosol; and

S3. identifying soot and a water-soluble aerosol in the sphericalaerosol based on a LiDAR ratio.

Further, step S1 includes: calculating an aerosol depolarization ratioADR, where when the ADR is greater than a, the aerosol components areconsidered to be the sand dust; when b≤ADR≤a, the aerosol components areconsidered to be the mixture of the sand dust and the spherical aerosol;or when the ADR is less than b, the aerosol components are considered tobe the spherical aerosol.

Further, the calculating the ADR includes: directing a LiDAR signalthrough a polarizer with a 45° polarization direction at a 532 nm signalusing a NIES Miescattering LiDAR system, to separate a horizontal signalfrom a vertical signal.

Further, a=0.31 and b=0.05.

Further, step S2 includes steps of:

S21. setting depolarization ratios of the sand dust and the sphericalaerosol as δ₁ and δ₂ respectively, and defining the depolarizationratios of the two components as δ_(i)=P_(i⊥)/P_(i∥), where P_(i⊥) andP_(i∥) are vertical and horizontal polarization components of an aerosolbackscattered signal respectively;

S22. defining δ_(i)′=P_(i⊥)/(P_(i⊥)+P_(i∥)), thenδ_(i)′=δ_(i)/(δ_(i)+1); and

S23. assuming that x represents an optical proportion of the sand dustin an aerosol mixture, where a polarization component of thebackscattered signal is expressed as:

P _(⊥) =[xδ ₁′+(1−x)δ₂ ′]P

P _(∥) =[x(1−δ₁′)+(1−x)(1−δ₂′)]P

where P=P_(⊥)+P_(∥), and therefore, the aerosol depolarization ratio δis expressed as:

$\delta = {\frac{P_{\bot}}{P_{\parallel}} = \frac{{x\delta}_{1}^{\prime} + {\left( {1 - x} \right)\delta_{2}^{\prime}}}{{x\left( {1 - \delta_{1}^{\prime}} \right)} + {\left( {1 - x} \right)\left( {1 - \delta_{2}^{\prime}} \right)}}}$

and therefore, the optical proportion of the sand dust x can becalculated using an equation:

$x = \frac{\left( {\delta - \delta_{2}} \right)\left( {1 + \delta_{1}} \right)}{\left( {1 + \delta} \right)\left( {\delta_{1} - \delta_{2}} \right)}$

Further, the aerosol depolarization ratio δ is obtained through thefollowing steps:

assuming

${R = \frac{\beta_{1} + \beta_{2}}{\beta_{2}}},$

where β₁ represents a backscattering coefficient of an aerosol particle,and β₂ represents a backscattering coefficient of an atmosphericmolecule; and

$\delta = \frac{{\left( {1 + \delta_{m}} \right)\delta_{v}R} - {\left( {1 + \delta_{v}} \right)\delta_{m}}}{{\left( {1 + \delta_{m}} \right)R} - \left( {1 + \delta_{v}} \right)}$

substituting R into the equation:

$\delta = \frac{{\left( {1 + \delta_{m}} \right)\delta_{v}R} - {\left( {1 + \delta_{v}} \right)\delta_{m}}}{{\left( {1 + \delta_{m}} \right)R} - \left( {1 + \delta_{v}} \right)}$

where δ_(v) represents a signal depolarization ratio, and δ_(m)represents a molecule depolarization ratio.

Further, β₁ is obtained through the following steps:

measuring the Miescattering caused by the aerosol and the Rayleighscattering caused by the atmospheric molecule separately, where a LiDARequation is expressed as

P(z)=CP ₀ z ⁻²[β₁(z)+β₂(z)]exp[−2∫₀ ^(z)σ₁(z)dz]exp[−2∫₀ ^(z)σ₂(z)dz]

where C represents a radar correction constant; P₀ represents radartransmission power; and β represents the backscattering coefficient, σrepresents an extinction coefficient, and subscripts of 1 and 2represent the aerosol particle and the atmospheric moleculerespectively;

assuming that a relationship between the extinction coefficient σ andthe backscattering coefficient β is as follows:

S=σ/β

and solving the foregoing LiDAR equation gives:

$\begin{matrix}{\beta_{1} = {{- \beta_{2}} + \frac{{X(z)}{\exp\left\lbrack {{- 2}\left( {S_{1} - S_{2}} \right){\int_{z_{c}}^{z}{{\beta_{2}(z)}{dz}}}} \right\rbrack}}{\begin{matrix}{\frac{X\left( z_{c} \right)}{{\beta_{1}\left( z_{c} \right)} + {\beta_{2}\left( z_{c} \right)}} -} \\{2S_{1}{\int_{z_{c}}^{z}{P(z)z^{2}{\exp\left\lbrack {{- 2}\left( {S_{1} - S_{2}} \right){\int_{z_{c}}^{z}{\beta_{2}\left( z^{\prime} \right){dz}^{\prime}}}} \right\rbrack}{dz}}}}\end{matrix}}}} & \end{matrix}$

where X(z)=P(z)z²; and β₁(z_(c)) and β₂(z_(c)) are boundary values at afar end z_(c).

Further, step S3 includes:

S31. establishing a lookup table 1 for the extinction coefficient σ withrespect to an extinction coefficient σ_(ws) of a water-soluble aerosoland an extinction coefficient σ_(st) of soot, and establishing anadditional lookup table 2 with respect to a case that the extinctioncoefficient is greater than 1;

S32. combining the lookup table for the extinction coefficient with theLiDAR ratio to establish a lookup table for a backscattering coefficientβ:

$\beta = {\frac{\sigma_{ws}}{S_{1}} + \frac{\sigma_{st}}{S_{2}}}$

S33. if 0<σ_(sphere)≤1, traversing the lookup table 1, or if1<σ_(sphere)≤3, traversing the lookup table 2, where σ_(sphere) is anextinction coefficient for the spherical aerosol, σ_(sphere) is thebackscattering coefficient; and retrieving an array of extinctioncoefficients from the lookup table whose errors relative to observedvalues meet a standard:

$\begin{matrix}{{❘\frac{\sigma_{sphere} - \sigma}{\sigma_{sphere}}❘} < 0.01} \\{{❘\frac{\beta_{sphere} - \beta}{\beta_{sphere}}❘} < 0.01}\end{matrix}$

and S34. if the lookup table does not match the observed values,selecting as an optimal solution a solution ensuring a minimum deviationbetween an observed value and a theoretical value, that is, a solutionmeeting the following condition:

$\min\left( \sqrt{{❘\frac{\sigma_{sphere} - \sigma}{\sigma_{sphere}}❘}^{2} + {❘\frac{\beta_{sphere} - \beta}{\beta_{sphere}}❘}^{2}} \right)$

Further, in step S33, the extinction coefficient σ_(sphere) of thespherical aerosol is equal to (1−x)σ.

Compared with the prior art, the present disclosure has the followingbeneficial effects.

During the existing atmospheric environment monitoring, it is onlypossible to determine whether there are the aerosol components, andamounts of contained aerosol components cannot be determined. Thepresent disclosure fills the gap in this field. In the prior art, toidentify the aerosol components, complex and expensive devices andcomplex operations are required, however, detection results are apt tobe inaccurate. On the contrary, in the present disclosure, only awavelength with a polarization channel is needed, to identify theaerosol components, achieving high accuracy with low detection costs.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a flowchart of a method for inverting aerosol components usinga LiDAR ratio and a depolarization ratio according to the presentdisclosure;

FIG. 2 is a diagram of testing a heavily polluted weather in a methodfor inverting aerosol components using a LiDAR ratio and adepolarization ratio according to the present disclosure; and

FIG. 3 is a diagram of testing a clear weather in a method for invertingaerosol components using a LiDAR ratio and a depolarization ratioaccording to the present disclosure.

DETAILED DESCRIPTION OF THE EMBODIMENTS

The specific embodiments of the present disclosure are further describedin detail with reference to the accompanying drawings. It should benoted here that the description of these embodiments is intended tofacilitate understanding of the present disclosure, but does notconstitute a limitation to the present disclosure. Further, thetechnical features involved in the various embodiments of the presentdisclosure described below may be combined with each other as long asthey do not conflict with each other.

As shown in FIG. 1, a method for inverting aerosol components using aLiDAR ratio and a depolarization ratio is provided, including steps of:S1. identifying sand dust, a spherical aerosol and a mixture of the sanddust and the spherical aerosol based on a depolarization ratio; S2.calculating a proportion of the sand dust in the mixture of the sanddust and the spherical aerosol; and S3. identifying soot and awater-soluble aerosol in the spherical aerosol based on a LiDAR ratio.

In a Fernald inversion method, Miescattering caused by the aerosol andRayleigh scattering caused by an atmospheric molecule are measuredseparately (Fernald, 1984), and therefore, a LiDAR equation may beexpressed as:

P(z)=CP ₀ z ⁻²[β₁(z)+β₂(z)]exp[−2∫₀ ^(z)σ₁(z)dz]exp[−2∫₀ ^(z)σ₂(z)dz]  (8)

where C represents a radar correction constant; P₀ represents radartransmission power; and β represents the backscattering coefficient, σrepresents an extinction coefficient, and subscripts of 1 and 2represent the aerosol particle and the atmospheric moleculerespectively.

To solve the equation, a relationship between the extinction coefficientand the backscattering coefficient needs to be assumed, that is, S=σ/β.In this case, the equation (8) can be solved:

$\begin{matrix}{\beta_{1} = {{- \beta_{2}} + \frac{{X(z)}{\exp\left\lbrack {{- 2}\left( {S_{1} - S_{2}} \right){\int_{z_{c}}^{z}{{\beta_{2}(z)}{dz}}}} \right\rbrack}}{\begin{matrix}{\frac{X\left( z_{c} \right)}{{\beta_{1}\left( z_{c} \right)} + {\beta_{2}\left( z_{c} \right)}} -} \\{2S_{1}{\int_{z_{c}}^{z}{P(z)z^{2}{\exp\left\lbrack {{- 2}\left( {S_{1} - S_{2}} \right){\int_{z_{c}}^{z}{\beta_{2}\left( z^{\prime} \right){dz}^{\prime}}}} \right\rbrack}{dz}}}}\end{matrix}}}} & (9)\end{matrix}$

where X(z)=P(z)z²; and β₁(z_(c)) and β₂(z_(c)) are boundary values at afar end z_(c) separately. Herein,

$S_{2} = \frac{8\pi}{3}$

is a fixed value for the atmospheric molecule. In addition, β₂ is knownfor an atmospheric model and meteorological observation. Herein, it isassumed that the LiDAR ratio S₁ of the aerosol is an empirical value of50 sr. When optical data of the aerosol provided by AERONET is accurate,the selected LiDAR ratio of the aerosol can also be adjusted based on acalculation result. Therefore, the extinction coefficient of the aerosolis calculated using the equation σ₁=50β₁.

The aerosol depolarization ratio (ADR) is different from the signaldepolarization ratio (SDR), and the SDR also covers Rayleigh scatteringof the atmospheric molecule. The ADR other than the SDR is required foran aerosol attribute characterized by LiDAR data at a low concentration.The aerosol depolarization ratio can be derived from the signaldepolarization ratio and the backscattering coefficient, it is assumedthat

${R = \frac{\beta_{1} + \beta_{2}}{\beta_{2}}},$

and therefore,

$\delta = \frac{{\left( {1 + \delta_{m}} \right)\delta_{v}R} - {\left( {1 + \delta_{v}} \right)\delta_{m}}}{{\left( {1 + \delta_{m}} \right)R} - \left( {1 + \delta_{v}} \right)}$

Substituting R into the foregoing equation gives:

$\begin{matrix}{\delta = \frac{{\left( {1 + \delta_{m}} \right)\delta_{\nu}R} - {\left( {1 + \delta_{\nu}} \right)\delta_{m}}}{{\left( {1 + \delta_{m}} \right)R} - \left( {1 + \delta_{\nu}} \right)}} & (10)\end{matrix}$

where δ_(v) represents the signal depolarization ratio; δ represents theaerosol depolarization ratio; and δ_(m) represents the moleculardepolarization ratio. Herein, 0.0044 is used for calculation. Herein, δ₁is obtained in the foregoing Fernald inversion method; and β₂ of theatmospheric molecule can be calculated based on meteorologicalobservation data. It should be noted that the ADR is vulnerable to noisein case of a small backscattering coefficient of the aerosol.

In the step of separating the sand dust from the spherical aerosol, itis considered that the sand dust is mixed with an external part of thespherical aerosol, and aerosol depolarization ratios are δ₁ and β₂separately. Herein, the depolarization ratios of the two components aredefined as δ_(i)=P_(i⊥)/P_(i∥), where P_(i⊥) and P_(i∥) are vertical andhorizontal polarization components of an aerosol backscattered signalrespectively. If it is defined that δ_(i)′=P_(i⊥)/(P_(i⊥)+P_(i∥)),δ_(i)′=δ_(i)/(δ_(i)+1). It should be noted that these parameters are allfunctions of height. If it is assumed that x represents an opticalproportion of the sand dust in an aerosol mixture, a polarizationcomponent of the backscattered signal can be expressed as:

P _(⊥) =[xδ ₁′+(1−x)δ₂ ′]P   (11)

P _(∥) =[x(1 −δ₁′)+(1−x)(1−δ₂′)]P   (12)

where P=P_(⊥)+P₈₁, and therefore, the aerosol depolarization ratio δ canbe expressed as:

$\begin{matrix}{\delta = {\frac{P\bot}{P_{}} = \frac{{x\delta_{1}^{\prime}} + {\left( {1 - x} \right)\delta_{2}^{\prime}}}{{x\left( {1 - \delta_{1}^{\prime}} \right)} + {\left( {1 - x} \right)\left( {1 - \delta_{2}^{\prime}} \right)}}}} & (13)\end{matrix}$

and therefore, the optical proportion of the sand dust x can becalculated using an equation:

$\begin{matrix}{x = \frac{\left( {\delta - \delta_{2}} \right)\left( {1 + \delta_{1}} \right)}{\left( {1 + \delta} \right)\left( {\delta_{1} - \delta_{2}} \right)}} & (14)\end{matrix}$

It should be noted that δ represents the aerosol depolarization ratiocalculated in the equation (10). As shown in Table 1, the depolarizationratio δ₁ of the sand dust and the depolarization ratio δ₂ of thespherical aerosol are 0.31 and 0.05 separately. The extinctioncoefficient σ_(ds) of the sand dust can be expressed as xσ, and theextinction coefficient σ_(sphere) of the spherical aerosol is expressedas (1−x)σ, where σ is the extinction coefficient of the aerosolcalculated in the foregoing Fernald method.

Because the water-soluble aerosol S₁ (47 sr) and the soot S₂ havesignificantly different LiDAR ratios (85 sr) as calculated in theMiescattering theory, that is, the two components have significantlydifferent ratios of extinction coefficients to backscatteringcoefficients, which can be used for distinguishing between the twocomponents. Specific operations are as follows:

(1) Establish a lookup table 1 for the extinction coefficient σ withrespect to an extinction coefficient σ_(ws) of the water-soluble aerosoland an extinction coefficient σ_(st) of the soot. The extinctioncoefficient ranges from 0 km⁻¹ to 1 km⁻¹, and an interval step of theextinction coefficient of the component is 0.001 km⁻¹. In addition, inconsideration of an actual situation, the extinction coefficient doesnot strictly ranges from 0 km⁻¹ to 1 km⁻¹ under a pollution condition.Therefore, it is necessary to establish an additional lookup table 2 ina case that the extinction coefficient is greater than 1, an upper limitof the extinction coefficient is 3 km⁻¹ (selected based on AERONETdata), and the interval step is 0.005 km⁻¹.

(2) Combine the lookup table for the extinction coefficient with theLiDAR ratio to establish a lookup table for a backscattering coefficientβ:

$\begin{matrix}{\beta = {\frac{\sigma_{ws}}{S_{1}} + \frac{\sigma_{st}}{S_{2}}}} & (15)\end{matrix}$

(3) Based on the extinction coefficient or σ_(sphere) and thebackscattering coefficient β_(sphere) of the spherical aerosolcalculated in the step of separating the sand dust from the sphericalaerosol, and if 0<σ_(sphere)≤1, traverse the lookup table 1; or if1<σ_(sphere)≤3, traverse the lookup table 2, to retrieve an array ofextinction coefficients from the lookup table whose errors relative toobserved values meet a standard.

$\begin{matrix}{{❘\frac{\sigma_{sphere} - \sigma}{\sigma_{sphere}}❘} < 0.01} & (16)\end{matrix}$ $\begin{matrix}{{❘\frac{\beta_{sphere} - \beta}{\beta_{sphere}}❘} < 0.01} & (17)\end{matrix}$

(4) If the lookup table does not match the observed values, select as anoptimal solution a solution ensuring a minimum deviation between anobserved value and a theoretical value, that is, a solution meeting thefollowing condition:

$\begin{matrix}{\min\left( \sqrt{\left. {{❘\frac{\sigma_{sphere} - \sigma}{\sigma_{sphere}}❘}^{2} + {❘\frac{\beta_{sphere} - \beta}{\beta_{sphere}}❘}^{2}} \right)} \right.} & (18)\end{matrix}$

In the present disclosure, the solution may be achieved in a method forinverting aerosol components using a LiDAR ratio and a depolarizationratio with a requirement of only a wavelength with a polarizationchannel. The method was applied to actually observed data of the LiDARin 2017, and the data in a heavily polluted weather (FIG. 2) and a cleanweather (FIG. 3) was calculated. Inversion results of aerosol componentsfrom January 2 to Jan. 4, 2017 are shown in FIG. 2. It can be seen thatunder the heavily polluted weather, the sand dust is not close to theground, and the water-soluble aerosol and the soot are dominant.Inversion results of aerosol components from January 8 to Jan. 10, 2017are shown in FIG. 3. Under the clean weather, there is almost no sanddust, the soot does not have a high concentration, and water-solubleaerosols such as sulfate and nitrate are dominant.

The embodiments of the present disclosure are described in detail abovewith reference to the accompanying drawings, but the present disclosureis not limited to the described embodiments. For a person skilled in theart, changes, modifications, replacements, and variations made to theseembodiments without departing from the principle and spirit of thepresent disclosure shall still fall within the protection scope of thepresent disclosure.

1. A method for inverting aerosol components using a LiDAR ratio and a depolarization ratio, comprising: S1. identifying sand dust, a spherical aerosol and a mixture of the sand dust and the spherical aerosol based on a depolarization ratio; S2. calculating a proportion of the sand dust in the mixture of the sand dust and the spherical aerosol; and S3. identifying soot and a water-soluble aerosol in the spherical aerosol based on a LiDAR ratio, wherein step S3 comprises: S31. establishing a lookup table 1 for the extinction coefficient σ with respect to an extinction coefficient σ_(ws) of a water-soluble aerosol and an extinction coefficient σ_(st) of soot, and establishing an additional lookup table 2 with respect to a case that the extinction coefficient is greater than 1; S32. combining the lookup table 1 and the lookup table 2 for the extinction coefficient with the LiDAR ratio to establish a lookup table 3 for a backscattering coefficient β: $\beta = {\frac{\sigma_{ws}}{S_{1}} + \frac{\sigma_{st}}{S_{2}}}$ S33. if 0<σ_(sphere)≤1, traversing the lookup table 1, or if 1<σ_(sphere)≤3, traversing the lookup table 2, wherein σ_(sphere) is an extinction coefficient for the spherical aerosol, σ_(sphere) is the backscattering coefficient; and retrieving an array of extinction coefficients from the lookup table 3 whose errors relative to observed values meet a standard: ${❘\frac{\sigma_{sphere} - \sigma}{\sigma_{sphere}}❘} < 0.01$ ${❘\frac{\beta_{sphere} - \beta}{\beta_{sphere}}❘} < 0.01$ and S34. if the lookup table 3 does not match the observed values, selecting as an optimal solution a solution ensuring a minimum deviation between an observed value and a theoretical value, that is, a solution meeting the following condition: $\min\left( {\sqrt{\left. {{❘\frac{\sigma_{sphere} - \sigma}{\sigma_{sphere}}❘}^{2} + {❘\frac{\beta_{sphere} - \beta}{\beta_{sphere}}❘}^{2}} \right)}.} \right.$
 2. The method for inverting aerosol components using a LiDAR ratio and a depolarization ratio according to claim 1, wherein step S1 comprises: calculating an aerosol depolarization ratio (ADR), wherein when the ADR is greater than 0.31, the aerosol components are considered to be the sand dust; when 0.05≤ADR≤0.31, the aerosol components are considered to be the mixture of the sand dust and the spherical aerosol; or when the ADR is less than 0.05, the aerosol components are considered to be the spherical aerosol.
 3. The method for inverting aerosol components using a LiDAR ratio and a depolarization ratio according to claim 2, wherein the calculating the ADR comprises: directing a LiDAR signal through a polarizer with a 45° polarization direction at a 532 nm signal using a NIES Miescattering LiDAR system, to separate a horizontal signal from a vertical signal.
 4. The method for inverting aerosol components using a LiDAR ratio and a depolarization ratio according to claim 1, wherein step S2 comprises: S21. setting depolarization ratios of the sand dust and the spherical aerosol as δ₁ and δ₂ respectively, and defining the depolarization ratios of the sand dust and the spherical aerosol as δ_(i)=P_(i⊥)/P_(i∥), wherein P_(i⊥) and P_(i∥) are vertical and horizontal polarization components of an aerosol backscattered signal respectively; S22. defining δ_(i)′=P_(i⊥)/(P_(i⊥)+P_(i∥)), then δ_(i)′=δ_(i)/(δ_(i)+1); and S23. assuming that x represents an optical proportion of the sand dust in an aerosol mixture, wherein a polarization component of the backscattered signal is expressed as: P _(⊥) =[xδ ₁′+(1−x)δ₂′]P P _(∥) =[x(1−δ₁′)+(1−x)(1−δ₂′)]P wherein P=P_(⊥)+P_(∥), and therefore, the aerosol depolarization ratio δ is expressed as: $\delta = {\frac{P_{\bot}}{P_{}} = \frac{{x\delta_{1}^{\prime}} + {\left( {1 - x} \right)\delta_{2}^{\prime}}}{{x\left( {1 - \delta_{1}^{\prime}} \right)} + {\left( {1 - x} \right)\left( {1 - \delta_{2}^{\prime}} \right)}}}$ and therefore, the optical proportion of the sand dust x can be calculated using an equation: $x = \frac{\left( {\delta - \delta_{2}} \right)\left( {1 + \delta_{1}} \right)}{\left( {1 + \delta} \right)\left( {\delta_{1} - \delta_{2}} \right)}$
 5. The method for inverting aerosol components using a LiDAR ratio and a depolarization ratio according to claim 4, wherein the aerosol depolarization ratio δ is obtained through the following steps: assuming ${R = \frac{\beta_{1} + \beta_{2}}{\beta_{2}}},$ wherein β₁ represents a backscattering coefficient of an aerosol particle, and β₂ represents a backscattering coefficient of an atmospheric molecule; and $\delta = \frac{{\left( {1 + \delta_{m}} \right)\delta_{v}R} - {\left( {1 + \delta_{v}} \right)\delta_{m}}}{{\left( {1 + \delta_{m}} \right)R} - \left( {1 + \delta_{v}} \right)}$ substituting R into the equation: $\delta = \frac{{\left( {1 + \delta_{m}} \right)\delta_{v}R} - {\left( {1 + \delta_{v}} \right)\delta_{m}}}{{\left( {1 + \delta_{m}} \right)R} - \left( {1 + \delta_{v}} \right)}$ wherein δ_(v) represents a signal depolarization ratio, and δ_(m) represents a molecule depolarization ratio.
 6. The method for inverting aerosol components using a LiDAR ratio and a depolarization ratio according to claim 5, wherein δ₁ is obtained through the following steps: measuring the Miescattering caused by the aerosol and the Rayleigh scattering caused by the atmospheric molecule separately, wherein a LiDAR equation is expressed as P(z)=CP ₀ z ⁻²[β₁(z)+β₂(z)]exp[−2∫₀ ^(z)σ₁(z)dz]exp[−2∫₀ ^(z)σ₂(z)dz] wherein C represents a radar correction constant; P₀ represents radar transmission power; and β represents the backscattering coefficient, σ represents an extinction coefficient, and subscripts of 1 and 2 represent the aerosol particle and the atmospheric molecule respectively; assuming that a relationship between the extinction coefficient σ and the backscattering coefficient β as follows: S=σ/β and solving the foregoing LiDAR equation gives: $\beta_{1} = {{- \beta_{2}} + \frac{{X(z)}{\exp\left\lbrack {{- 2}\left( {S_{1} - S_{2}} \right){\int_{z_{c}}^{z}{{\beta_{2}(z)}dz}}} \right\rbrack}}{\frac{X\left( z_{c} \right)}{{\beta_{1}\left( z_{c} \right)} + {\beta_{2}\left( z_{c} \right)}} - {2S_{1}{\int_{z_{c}}^{z}{{P(z)}z^{2}{\exp\left\lbrack {{- 2}\left( {S_{1} - S_{2}} \right){\int_{z_{c}}^{z}{{\beta_{2}\left( z^{\prime} \right)}{dz}^{\prime}}}} \right\rbrack}{dz}}}}}}$ wherein X(z)=P(z)z²; and β₁(z_(c)) and β₂(z_(c)) are boundary values at a far end z_(c).
 7. The method for inverting aerosol components using a LiDAR ratio and a depolarization ratio according to claim 1, wherein in step S33, the extinction coefficient σ_(sphere) of the spherical aerosol is equal to (1−x)σ. 